A variety of methods have been proposed to improve classification accuracy. ML and DL approaches were explored in the recent past. Most popular ML techniques are Support Vector Machines (SVM) and decision tree [1]}, feature engineering [2]} and spectral analysis[3]}, though this often limits the classification scope. Apart from this DL based architectures are popular and shown state-of-the-art results. Different Dense Neural Network (DNN), Convolution Neural Network (CNN) [4]} and Long Short Term Memory (LSTM) [5]} based architectures are proposed for better classification [6]} [7]}.DL based classification shown better accuracy for AFib detection[8]}[9]} [10]}.
